Detection & Diagnostic Systems Multimedia

The Millimeter-Wave Remote Biometric Identification and Tracking
(mmW RBIT) System for Security Applications addresses one of the nation’s top homeland
security concerns: the need for real-time, remote surveillance of aspects of human behavior
to help identify terrorists. Such monitoring involves the collection, measurement, and interpretation
of biometric data from individuals, such as their heart rate, breathing rate, and movement.
This mission of conducting constant surveillance on a large number of human subjects is difficult
and complex. It needs to be performed at a variety of critical locations (e.g., airports,
border portal entrances, cargo inspection harbors), so the machine should be portable, easy
to deploy, and able to operate in all types of weather. The task is especially difficult
because the human targets are moving and should not know they are being monitored; thus,
automated motion tracking and biometric surveillance from a distance are required. The tool
must be noninvasive (i.e., not touch the target) and work through clothing and perhaps walls.
It must provide accurate results almost immediately. This system has two other critically
important applications: It could be used in the battlefield and at disaster sites to aid
in triage and response and recovery operations.

Figure 1. mmWRBIT system (left) and some potential applications (right): Top graphic illustrates
the principal biometric security application for remote tracking, identification, and
stimulus response characterization; middle graphic shows how it might be used in a
hospital or home healthcare application, for remote monitoring and diagnostics based
on heartbeats, respiration, and movements in real time; and the bottom graphic indicates
its use after a disaster to assist in search and rescue operations.
Click on image to view larger image.

We developed this first remote heartbeat, respiration, and body motion identification and
tracking system on the basis of modern mmW techniques. Some of its beneficial features and
capabilities are:

Novel: It’s the first system to remotely identify and persistently track a subject
while recording his or her heartbeat, respiration, and movement.

Nonintrusive: It senses
through clothing and many common optically opaque materials, including masonry.

Able
to conduct long-range surveillance: It can take measurements from tens of meters away,
and the camera maintains its aim when obstructions partially or temporarily block its field
of view.

Operates under harsh conditions: It works in darkness and daylight and is not
affected by atmospheric conditions, such as moisture, dust, and smoke.

Portable: The entire system can be rapidly deployed and adapted to covert operations.

Reliable and secure: It uses advanced feature-extraction and data-analysis algorithms
that are nearly 100% accurate in identifying humans and more than 98.8% accurate in identifying
heartbeat and respiration patterns.

Adaptable: It can be integrated with existing vision-based biometric and video
surveillance systems.

Many potential applications: It can be used for biometrics security, battlefield
triage, to search for vital signs after disasters, to monitor a patient’s heart condition and movement,
to combat identity theft, for on-line monitoring of operating machinery, and to monitor vehicles to avoid
collisions.

Figure 2. Results from an experiment on a moving male subject (There is excellent agreement between the heartbeat data extracted by the mmWRBIT system [red] and the data detected by an ECG [green].)
Click on image to view larger image.

The mmWRBIT product is a combination of three interoperational subsystems:

a 94-GHz
mmW interferometric Doppler displacement sensor;

a depth sensor and an optical video
camera tracking subsystem; and

real-time, interactive, graphical user interface (GUI)
software.

With the aid of the depth sensor and optical video camera tracking subsystem,
the servo control system guides (rotates and tilts) the mmW Doppler displacement sensor
to the appropriate location near the heart of the subject, and the real-time software analyzes
the reflected mmW signal with feature-recognition algorithms, providing persistent monitoring
of the subject’s biometric measurements.